西電數字圖像處理上機報告

1、數字圖像處理上機報告實驗一一、實驗目的1熟悉有關數字圖像處理的MATLAB基本操作和編寫；2掌握數字圖像的基本讀寫、顯示與保存；3能夠利用MATLAB工具箱完成圖像處理的基本運算；二、實驗內容1（1）讀取圖像并顯示真彩色圖像house.tiff；（2）讀取圖像并顯示索引色圖像canoe.tif，并轉換為灰度圖像；（3）讀取圖像并顯示灰度圖像rice.png，并轉換為二進制圖像；（4）檢測內存中的圖像和保存圖像；2查看不同分辨率下圖像lena.tiff的顯示結果；3對彩色圖像Peppers.png觀看GRB通道各單通道圖像；4實現馬赫帶效應并畫出灰度直方圖。程序如下：clear allclose

2、 allclc%Task1%讀取圖像并顯示真彩色圖像%讀入圖像img_house=imread('house.tiff');figure('NumberTitle', 'off', 'Name', '真彩House');imshow(img_house)%Task2%讀取圖像并顯示索引色圖像，并轉換為灰度圖像；%讀入圖像img_canoe,MAP_canoe=imread('canoe.tif');figure('NumberTitle', 'off', 'N

3、ame', '索引Canoe');imshow(img_canoe,MAP_canoe)gray_canoe = ind2gray(img_canoe,MAP_canoe);figure('NumberTitle', 'off', 'Name', '灰度Canoe');imshow(gray_canoe);%Task3%讀取圖像并顯示灰度圖像，并轉換為二進制圖像%讀入圖像img_rice=imread('rice.png');figure('NumberTitle', 

4、9;off', 'Name', '灰度Rice');imshow(img_rice)bw_rice = im2bw(img_rice);figure('NumberTitle', 'off', 'Name', '二進制Rice');imshow(bw_rice);%Task4%讀取圖像-保存圖像-重新讀取保存的圖像%讀入圖像img_rice=imread('rice.png');figure('NumberTitle', 'off', '

5、;Name', 'Read Image Rice');imshow(img_rice)imwrite(img_rice,'RiceImg_Write','TIFF');img_rice_Rre=imread('RiceImg_Write','TIFF');figure('NumberTitle', 'off', 'Name', 'Reread Rice');imshow(img_rice_Rre);%Task4%讀取圖像并顯示真彩色圖像%讀入圖

6、像img_lena=imread('lena.tiff');figure('NumberTitle', 'off', 'Name', 'Lena');imshow(img_lena)small_lena = imresize(img_lena, 0.1);%圖像縮放figure('NumberTitle', 'off', 'Name', 'Small Lena');imshow(small_lena)big_lena = imresize(img_le

7、na, 0.7);%圖像縮放figure('NumberTitle', 'off', 'Name', 'Big Lena');imshow(big_lena)%Task5%對彩色圖像Peppers.png觀看GRB通道各單通道圖像%讀入圖像I = imread('Peppers.png');R=I;R(:,:,2 3)=0;G=I;G(:,:,1 3)=0;B=I;B(:,:,1 2)=0;figure,imshow(R);figure,imshow(G);figure,imshow(B);%Task4%實現馬赫帶

8、效應并畫出灰度直方圖imsize_x=300;%圖像大?。ㄕ叫危﹊msize_y=300;n=7;%馬赫帶個數img_machbands=zeros(imsize_x,imsize_y);for i=1:n img_machbands(:,fix(imsize_y*(i-1)/n)+1:fix(imsize_y*i/n)=255*(i-1)/n;endimg_machbands=uint8(img_machbands);figure('NumberTitle', 'off', 'Name', 'Mach Bands');imsh

9、ow(img_machbands);figure('NumberTitle', 'off', 'Name', 'Mach Bands Hist');imhist(img_machbands);結果如下：實驗二一、實驗目的1熟悉有關MATLAB工具箱中提供的圖像變換函數；2掌握傅立葉變換和小波變換等常用的正交變換函數；二、實驗內容1對圖像lena.png進行傅立葉變換和離散余弦變換，并分別求出其逆變換后重構圖像的均方誤差；2實現圖像lena.png的兩層小波分解，觀察分解系數并重構，求重構圖像誤差值；3觀察圖像IM1.BMP經小波分

10、解系數的方向性，實現三層小波分解，分別把HL,LH,HH子帶置零和重構，觀察重構圖像跟原始圖像的差異。程序如下：clear allclose allclc% FFT% 傅立葉變換和離散余弦變換，并分別求出其逆變換后重構圖像的均方誤差%讀入圖像img_lena=imread('lena.png');figure('NumberTitle', 'off', 'Name', 'Lena');imshow(img_lena)%FFT變換%img_lena_fft=fft2(img_lena);spectrum = ffts

11、hift(abs(img_lena_fft);spectrum = 255*spectrum/max(spectrum(:);figure('NumberTitle', 'off', 'Name', 'Lena Spectrum');spectrum=uint8(spectrum);imshow(spectrum);%iFFT變換%img_lena_ifft=real(ifft2(img_lena_fft);%進行反變換img_lena_ifft=uint8(img_lena_ifft);figure('NumberTit

12、le', 'off', 'Name', 'Lena iFFT Recovery');imshow(img_lena_ifft);%圖像還原誤差%deviation=norm(double(img_lena_ifft-img_lena)2;text(100,100,num2str(deviation),'FontSize',18,'Color','b')%DCT變換%I = img_lena;img_lena_dct = dct2(I);figure('NumberTitle'

13、, 'off', 'Name', 'Lena DCT Spectrum');imshow(log(abs(img_lena_dct),), colormap(jet), colorbar%iDCT變換% % J(abs(J)<10) = 0;%去掉部分信息img_lena_idct = idct2(img_lena_dct);figure('NumberTitle', 'off', 'Name', 'Lena iDCT Recovery');imshow(img_lena_id

14、ct,0 255)%圖像還原誤差%deviation_dct=norm(double(img_lena_idct-double(img_lena)2;text(100,100,num2str(deviation_dct),'FontSize',18,'Color','b')% Wavelet% 小波變換與反變換,實現圖像lena.png的兩層小波分解，觀察分解系數并重構，求重構圖像誤差值 Lo_D,Hi_D,Lo_R,Hi_R = wfilters('db1');%生成小波變換以及反變換所需的低通高通濾波器N=2;%2層小波變換C

15、,S = wavedec2(img_lena,N,Lo_D,Hi_D);%小波變換分層分開顯示ca1=wcodemat(appcoef2(C,S,'db1',1),255);ch1=wcodemat(detcoef2('h',C,S,1),255);cv1=wcodemat(detcoef2('v',C,S,1),255);cd1=wcodemat(detcoef2('d',C,S,1),255);% c1=uint8(ca1,ch1;cv1,cd1);% figure('NumberTitle', 'of

16、f', 'Name', 'Lena Wavelet Level 1');% imshow(c1);ca2=wcodemat(appcoef2(C,S,'db1',2),255);ch2=wcodemat(detcoef2('h',C,S,2),255);cv2=wcodemat(detcoef2('v',C,S,2),255);cd2=wcodemat(detcoef2('d',C,S,2),255);% c2=uint8(ca2,ch2;cv2,cd2);% figure('Num

17、berTitle', 'off', 'Name', 'Lena Wavelet Level 2');% imshow(c2);%小波變換兩層結果同時顯示L2 = ca2,ch2;cv2,cd2;k=S(2,1)*2-S(3,1);ch1 = padarray(ch1,k k,1,'post');%保護原有數據矩陣cv1 = padarray(cv1,k k,1,'post');cd1 = padarray(cd1,k k,1,'post');L = L2,ch1; cv1,cd1;%將第二層

18、小波變換結果添加到第一層小波變換結果上figure('NumberTitle', 'off', 'Name', 'Lena Wavelet L2');imshow(L,'InitialMagnification',100);%小波反變換% img_iwavelet = waverec2(C,S,Lo_R,Hi_R);figure('NumberTitle', 'off', 'Name', 'Lena iWavelet Recovery');imshow

19、(uint8(img_iwavelet);%圖像還原誤差%deviation_wavelet=norm(double(img_iwavelet-double(img_lena)2;text(100,100,num2str(deviation_wavelet),'FontSize',18,'Color','b')% Wavelet % 觀察圖像IM1.BMP經小波分解系數的方向性，實現三層小波分解，分別把HL,LH,HH子帶置零和重構，觀察重構圖像跟原始圖像的差異。%讀入圖像img_im1=imread('IM1.BMP');fig

20、ure('NumberTitle', 'off', 'Name', 'TM1 Source Image');imshow(img_im1)C,S=wavedec2(double(img_im1),3,'db1');ca3 = appcoef2(C,S,'db1',3);ch3 = detcoef2('h',C,S,3);cv3 = detcoef2('v',C,S,3);cd3 = detcoef2('d',C,S,3);ch2 = detcoef2(

21、'h',C,S,2);cv2 = detcoef2('v',C,S,2);cd2 = detcoef2('d',C,S,2);ch1 = detcoef2('h',C,S,1);cv1 = detcoef2('v',C,S,1);cd1 = detcoef2('d',C,S,1);% L3 = ca3*4,ch3*4;cv3*4,cd3*4;L3 = ca3,ch3;cv3,cd3;k=S(2,1)*2-S(3,1);ch2 = padarray(ch2,k k,1,'post');

22、cv2 = padarray(cv2,k k,1,'post');cd2 = padarray(cd2,k k,1,'post');% L2= L3,ch2*4; cv2*4,cd2*4;L2= L3,ch2; cv2,cd2;k=S(2,1)*4-S(4,1);ch1 = padarray(ch1,k k,1,'post');cv1 = padarray(cv1,k k,1,'post');cd1 = padarray(cd1,k k,1,'post');% L = L2,ch1*4; cv1*4,cd1*4;L

23、 = L2,ch1; cv1,cd1;figure('NumberTitle', 'off', 'Name', 'Lena Wavelet L3');imshow(L,'InitialMagnification',100);%LH置零%ca3 = appcoef2(C,S,'db1',3);ch3 = detcoef2('h',C,S,3);cv3 = detcoef2('v',C,S,3);cd3 = detcoef2('d',C,S,3);ch2 =